Bibliographic record
Abstract
Victor A. Snieckus, 83, died Dec. 18, 2020, in Kingston, Ontario. “Following a highly productive 30-year career at the University of Waterloo, when Vic and his students were instrumental in the development and applications of the directed ortho metalation reaction, he moved to Queen’s University in Ontario in 1998 to accept the Bader Chair in Chemistry. For the next 2 decades, Vic continued to expand and link metalation chemistry with transition-metal-catalyzed cross-coupling methodologies. Vic’s joie de vivre was infectious and tireless. As anyone who met him can attest, he was an extreme and inclusive extrovert, was a constant presence at conferences—always with probing and insightful questions of speakers—and could make friends in any circumstance.”—P. Andrew Evans, James R. Green, and Gordon W. Gribble, colleagues and friends Most recent title: Professor of chemistry and Emeritus Bader Chair in Chemistry, Queen’s University Education: BSc, chemistry, University of Alberta, 1959; MSc, organic chemistry,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".